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Since the late 1980s, social theorists championed for the birth of a new era, in which societies were increasingly exposed to growing global risks. The presence of increasing risks including natural disasters, technological errors, terrorist attacks, nuclear wars and environmental degradation suggests that human beings are becoming increasingly vulnerable. Therefore, an understanding of vulnerability is crucial. Vulnerability is often considered as the potential to suffer from physical attacks. This approach, however, has limited capacity to explain many forms of suffering including not only physical aspects, but also mental, social, economic, political and social dimensions. This chapter draws on the vulnerability literature to present an overarching framework for the book. It starts with an outline of the concept origins, then discusses its relationship with the risk society thesis before forming conceptualisation. The chapter then points out the key similarities and differences between vulnerability and other concepts such as risk, disaster, poverty, security and resilience. The authors rework an existing “security” framework to develop a new definition of the concept of vulnerability. Finally, the authors look into the root causes and the formation of vulnerability within social systems.

The purpose of this paper is to develop a novel integrated risk assessment method from the system perspective to evaluate the risk of the cross-regional mega construction project (CMCP). Furthermore, this paper aims to confirm the core risk source factors and refine the risk management strategies of CMCPs through a case study.

Based on the analysis of the risk system of CMCPs, the concept model and risk assessment principles of integrated risk assessment were confirmed. The risk source factors and project objectives of the CMCP were identified from a literature review, export interview and case analysis. According to the vulnerability theory, the integrated risk assessment model was developed by involving vulnerabilities, threats, objectives and interaction of those factors synthetically. Then, ZW high-speed railway from China was analyzed to verify the feasibility and effectiveness of the proposed method.

As a result, 12 threat factors and 12 vulnerability factors were identified. Based on the case study, the main external threat comes from T13 (conflicts of interest between local governments) and T23 (harsh natural environment); the most easily exploited internal vulnerabilities were V11 (complexity of technology), V13 (lack of experience in technical application), V21 (inadequate experience) and V23 (lack of interest coordination mechanism). Moreover, the economic objective was most affected.

It is essential to develop an interest coordination mechanism for CMCPs. The harsh natural environment is a critical factor, but it also promotes technological innovation and iteration. Public opinions in different regions are critical for CMCPs, and more emphasis should be placed on public opinion surveys of CMCPs. Moreover, diverse and flexible environmental protection strategies should apply in CMCPs.

This research has the following three contributions. First, based on vulnerability theory, an integrated risk assessment approach of CMCPs is developed, which enriches the risk measurement method system and provides inspiration for future research on risk in the construction industry. Second, the risk sources of CMCPs are identified from the perspective of vulnerability and threat to provide clear guidance for the risk management of CMCPs. Third, the core risk source factors and management strategies confirmed by the case study will be beneficial for various governments in different regions and project managers to optimize the project management scheme, as they are transferable management experiences.

This paper aims to illustrate how the climate change‐vulnerability‐risk model (CCVRM) can be used to analyze the changes in system vulnerabilities and risks, as a result of implementing a community‐based early warning system (EWS).

The CCVRM is used to examine the community‐based EWS being implemented in the municipalities of Infanta and General Nakar in Quezon Province, Philippines. The levels of vulnerabilities and risks of the two localities are assessed through qualitative analysis using the CCVRM as framework. The model is also used to analyze the effects of the EWS in addressing the localities' vulnerabilities and risks.

Technological and institutional vulnerabilities of the Infanta and General Nakar systems have lessened when the EWS project was implemented. Technological and institutional vulnerabilities have direct correlations with mortality risk; thus, when the levels of the former decrease, so does the latter. Although the reduced technological and institutional vulnerabilities have an effect on the other type of risks present in the municipalities, the effects were not as significant as that of with mortality risk.

Due to limited time and resources, only one adaptation program is analyzed, specifically, the community‐based EWS being implemented in the municipalities of Infanta and General Nakar, Philippines. An integrated analysis of different measures is not done. Although investigating a multi‐adaptation program is possible, this would require more time and resources to implement. Likewise, only a simple evaluation based on model definitions is conducted, instead of a more extensive risk and vulnerability assessment.

The CCVRM acts as an analytical guide in understanding the effects of climate change adaptive measures. Accordingly, this paper investigates the effects of an implemented adaptive measure. The study also shows how the CCVRM can be used to analyze planned measures and identify the types of risks and vulnerabilities that this type of adaptive measure can influence.

The purpose of this paper is to analyze flood vulnerability vis-à-vis flood-induced health risks, and understand the relationship between them to suggest measures to reduce health risks in Sudan.

This study compares the vulnerability to flood and health consequences in two communities in Aroma. This study compares the vulnerability of Aroma semi-urban vicinity and Tendellei rural village, in Sudan, to flood and health consequences. A set of socioeconomic and health indicators were studied in 251 households. Households were classified according to their calculated vulnerability composite index. The index was validated through comparing the vulnerability values with the level of impact in each household.

About 30 percent of households are highly/very highly vulnerable to flood risk. On the other hand, 41 percent of the rural households and 25 percent of the semi-urban houses are highly/very highly vulnerable to health risks. The main determinants of flood vulnerability are; the number of earning family members, level of education and economic activity of the household's head. The rural households are found to be more vulnerable to health risks while semi-urban households are more vulnerable to flooding. Flood and health vulnerabilities are positively correlated. Factors like urbanization, poverty and education directly affect the vulnerability of communities.

The methodology could be strengthened through the running of multi-various regression to relate selected vulnerability indicators to incidence of malaria and diarrhea in each household.

The method described in this paper is flexible; applicable and can be reproduced for other areas and risks.

Vulnerability determinants affect the two communities differently and this necessitates specific consideration when developing policy. The policy should tackle the root causes of vulnerability to cut the vicious circle of poverty, illiteracy and illness. Those root causes should be managed by integrating multi-hazard approaches for effective and efficient interventions.

The method described in this paper is original, flexible; applicable and can be reproduced for other areas and risks.

This paper aims to design a vulnerability assessment model considering the multidimensional and systematic approach to disaster risk and vulnerability. This model serves to both risk mitigation and disaster preparedness phases of humanitarian logistics.

A survey of 27,218 households in Pueblo Rico and Dosquebradas was conducted to obtain information about disaster risk for landslides, floods and collapses. We adopted a cross entropy-based approach for the measure of disaster vulnerability (Kullback–Leibler divergence), and a maximum-entropy estimation for the reconstruction of risk a priori categorization (logistic regression). The capabilities approach of Sen supported theoretically our multidimensional assessment of disaster vulnerability.

Disaster vulnerability is shaped by economic, such as physical attributes of households, and health indicators, which are in specific morbidity indicators that seem to affect vulnerability outputs. Vulnerability is heterogeneous between communities/districts according to formal comparisons of Kullback–Leibler divergence. Nor social dimension, neither chronic illness indicators seem to shape vulnerability, at least for Pueblo Rico and Dosquebradas.

The results need a qualitative or case study validation at the community/district level.

We discuss how risk mitigation policies and disaster preparedness strategies can be driven by empirical results. For example, the type of stock to preposition can vary according to the disaster or the kind of alternative policies that can be formulated on the basis of the strong relationship between morbidity and disaster risk.

Entropy-based metrics are not widely used in humanitarian logistics literature, as well as empirical data-driven techniques.

The vulnerability issue in supply chains is among the most pressing concerns that firms are currently facing. As a preliminary attempt to address the lack of empirical research, this paper aims to primarily explore the relationship between vulnerability mitigation strategies and supply chain effectiveness with security culture as a moderator.

Data are gathered via a survey of 209 Indonesian manufacturing firms. The data are analyzed using partial least squares technique.

Results indicate that supply chain visibility, supply chain flexibility and supplier development strategies positively affect supply chain effectiveness. Moreover, risk culture positively moderates the effects of supply chain visibility and supplier development on supply chain effectiveness.

The findings may improve supply chain effectiveness by mitigating the effects of vulnerability causes.

This study contributes to the advancement of knowledge on the relationships between vulnerability mitigation strategies and supply chain effectiveness.

In any information security risk assessment, vulnerabilities are usually identified by information‐gathering techniques. However, vulnerability identification errors – wrongly identified or unidentified vulnerabilities – can occur as uncertain data are used. Furthermore, businesses' security needs are not considered sufficiently. Hence, security functions may not protect business assets sufficiently and cost‐effectively. This paper aims to resolve vulnerability errors by analysing the security requirements of information assets in business process models.

Business process models have been selected for use, because there is a close relationship between business process objectives and risks. Security functions are evaluated in terms of the information flow of business processes regarding their security requirements. The claim that vulnerability errors can be resolved was validated by comparing the results of a current risk assessment approach with the proposed approach. The comparison is conducted both at three entities of an insurance company, as well as through a controlled experiment within a survey among security professionals.

Vulnerability identification errors can be resolved by explicitly evaluating security requirements in the course of business; this is not considered in current assessment methods.

It is shown that vulnerability identification errors occur in practice. With the explicit evaluation of security requirements, identification errors can be resolved. Risk assessment methods should consider the explicit evaluation of security requirements.

This research aims to develop a model that may be used to determine the effective adaptive measures to implement in a system affected by climate change.

The three primary dimensions of the model were individually investigated and then the linkages among them were developed. Specifically, the nature of climate change was examined and the issues emerging from the changes were analyzed. Next, an intensive study of system vulnerabilities was conducted, and the third factor in the model, risk, is then explored. Afterwards, the conceptual framework, which is the foundation of the climate change vulnerability risk model, was devised and the model created.

The model is a three‐dimensional matrix with the nature of climate change, vulnerabilities, and risks as its chief dimensions. It identifies the four natures of climate change, namely: variability, intensity, frequency, and quantity and the vulnerability types to be socio‐economic, biophysical, technological, and institutional. Meanwhile, risks are classified as income, biodiversity, health, mortality, and infrastructure risks.

The research is the first phase of a three‐stage study on the linkages among climate change, vulnerability, and risks. It is the development stage of the framework that exemplifies the interrelationships among these variables and is the basis of the statistical and econometric analyses in the later stages.

The climate change vulnerability risk model was developed to act as an analytical guide in understanding the effects of climate change to systems. The model may be used to determine the effective adaptive measures to apply in the system, through a comparative analysis of the variables in the matrix.

Purpose – The vulnerability and adaptive capacities of cities in Latin America have received relatively less attention compared to other regions of the world. This chapter seeks to address these gaps by (a) examining vulnerability to the health impacts from air pollution and temperature, and exploring whether socioeconomic factors between neighborhoods differentiate these risks within the cities of Bogota, Buenos Aires, Mexico City, and Santiago and (b) assessing the capacity of urban populations to perceive and respond to vulnerability and risk.

Design/methodology/approach – Because of the complex nature of vulnerability, we combined a set of quantitative and quantitative methods and data to determine whether and under what conditions the people in these cities are vulnerable (e.g., Time Series Analysis, Generalized Linear Model, and statistical correlations of exposure and human mortality with socioeconomic vulnerability).

Findings – We found high levels of PM10, ozone, and other criteria air pollutants in three cities for which we had data. However, the pattern of their impacts on health depends on the particulars of pollutant levels and atmospheric and weather conditions of each city. Our results reflect the varied facets of urban vulnerability and shed light on the nature of the associated human health risks. Although wealthy populations have access to education, good quality housing, and health services to mitigate some environmental risks, overall the data show that health impacts from air pollution and temperature in the study cities do not necessarily depend on socioeconomic differentiations.

Research limitations/implications – Although we sought to use quantitative and qualitative methods, given the complexity of the research, it has proven difficult to fully explore these issues across scales and with a full accounting of local context.

Practical implications – Our findings show that wealthy and educated populations may be equally at risk to the health implications of air pollution. Policies designed to mitigate these risks should not use socioeconomic characteristics as predictors of a population's risk in relation to air pollution.

Originality/value – This research contributes valuable insights into the dynamics of vulnerability to air pollution in Latin American cities, a region that has been historically underrepresented in empirical studies of urban risk. We have also combined a range of methods and approaches to improve our understanding of the multifaceted nature of urban vulnerability to global environmental change.

Malicious attackers frequently breach information systems by exploiting disclosed software vulnerabilities. Knowledge of these vulnerabilities over time is essential to decide the use of software products by organisations. The purpose of this paper is to propose a novel G-RAM framework for business organisations to assess and mitigate risks arising out of software vulnerabilities.

The G-RAM risk assessment module uses GARCH to model vulnerability growth. Using 16-year data across 1999-2016 from the National Vulnerability Database, the authors estimate the model parameters and validate the prediction accuracy. Next, the G-RAM risk mitigation module designs optimal software portfolio using Markowitz’s mean-variance optimisation for a given IT budget and preference.

Based on an empirical analysis, this study establishes that vulnerability follows a non-linear, time-dependent, heteroskedastic growth pattern. Further, efficient software combinations are proposed that optimise correlated risk. The study also reports the empirical evidence of a shift in efficient frontier of software configurations with time.

Existing assumption of independent and identically distributed residuals after vulnerability function fitting is incorrect. This study applies GARCH technique to measure volatility clustering and mean reversal. The risk (or volatility) represented by the instantaneous variance is dependent on the immediately previous one, as well as on the unconditional variance of the entire vulnerability growth process.

The volatility-based estimation of vulnerability growth is a risk assessment mechanism. Next, the portfolio analysis acts as a risk mitigation activity. Results from this study can decide patch management cycle needed for each software – individual or group patching. G-RAM also ranks them into a 2×2 risk-return matrix to ensure that the correlated risk is diversified. Finally the paper helps the business firms to decide what to purchase and what to avoid.

Contrary to the existing techniques which either analyse with statistical distributions or linear econometric methods, this study establishes that vulnerability growth follows a non-linear, time-dependent, heteroskedastic pattern. The paper also links software risk assessment to IT governance and strategic business objectives. To the authors’ knowledge, this is the first study in IT security to examine and forecast volatility, and further design risk-optimal software portfolios.